Discussions about analytics usually focus on how they can help businesses slice and dice customer behaviors, market trends, manufacturing processes and the like. However, as more people at all levels of the organization become aware of their potential, analytics are being applied to areas that might not be at the top of most managers’ minds.
In fact, data scientists are finding all sorts of ways to use analytics to help make better decisions in areas of the company that you might not expect, from training to workforce development to real estate. For example:
The proof of training’s effectiveness can be found in the numbers.
- Corporate training. “Learning analytics” can help companies determine if their educational efforts are paying off. Recently, Chrysler reviewed data from more than 33,000 salespeople to get a sense not only of whether its sales-training efforts were working, but in what areas they were proving most effective. The automaker’s analysis, which was conducted by the consulting firm Vestrics, showed that its program led to an increase in sales of 1.3 vehicles a month, per salesperson. It also demonstrated training’s impact on retention: The retention rate of trained salespeople was 98.9%, compared to 47.8% for those who didn’t receive training. In addition, turnover was lower for new hires who were trained early.
- Facilities location decisions. Before one company in Pennsylvania moved its headquarters, executives looked at the impact the move would have on their employees. Because the distance involved wasn’t very far, they didn’t expect to uncover any issues. In reality, they found that the move would cause enough disruption to employee commutes to impact child care and other family issues with enough force to cause a number of workers to seek jobs elsewhere. Further study showed that any savings realized from the move would be offset by the expense of recruiting new employees. The firm stuck to its original location.
Analytics can identify hidden costs involved in facilities changes and relocations.
- Call centers. Analytics can stretch beyond current applications in areas where they’re already in use. For example, applying predictive analytics to data compiled from call records can help identify which customers are most interested in a company’s new product, so the sales and marketing departments can be proactive in their outreach. By “listening in” on calls, systems can identify keywords in conversations that indicate whether a caller is happy or dissatisfied, and so guide the call center representative toward a proper response and ultimately a resolution of any issues.
A combination of advancing technology, more robust tools and a growing awareness of analytics in general is pushing awareness of data’s value into new areas of business, and encouraging more managers to envision new applications for it. It’s a good reason to have data scientists familiarize themselves with all aspects of your company – even the ones where you might think analytics can’t be applied.